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对统计学习理论的研究背景和发展历史进行介绍,总结前人有关基于核的正则化学习算法的研究动态以及已取得的成果。给出正则化在线学习算法的定义,针对不同的抽样背景得出研究正则化在线学习算法的一致性及误差界的方法。
The research background and development history of statistical learning theory are introduced, and the previous research on kernel-based regularization learning algorithm and its achievements have been summarized. The definition of regularization online learning algorithm is given. The consistency and error bounds of regularization online learning algorithm are obtained for different sampling backgrounds.